In the 1990’s, executives became less concerned with the day-to-day business operations and more concerned with overall business functions.
Data warehouse – a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks.
The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes
Extraction, transformation, and loading (ETL) – a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse.
Data mart – contains a subset of data warehouse information.
Databases contain information in a series of two-dimensional tables.
In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows
Dimension – a particular attribute of information.
Cube – common term for the representation of multidimensional information.
Data mining – the process of analyzing data to extract information not offered by the raw data alone.
To perform data mining, users need data-mining tools.
Data-mining tool – uses a variety of techniques to find patterns and relationships in large volumes of information and infers rules that predict future behavior and guide decision making.
Information Cleansing or Scrubbing
Meaning : a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information.
Contact information in an operational system :
Standardizing Customer name from Operational Systems :
Information cleansing activities :
Accurate and complete information :
Business Intelligence
Meaning : information that people use to support their decision-making efforts
Principle BI enablers include:
1. Technology
Even the smallest company with BI software can do sophisticated analyses today that were unavailable to the largest organizations a generation ago.
The largest companies today can create enterprisewide BI systems that compute and monitor metrics on virtually every variable important for managing the company.
How is this possible? The answer is technology—the most significant enabler of business intelligence.
2. People
Understanding the role of people in BI allows organizations to systematically create insight and turn these insights into actions.
Organizations can improve their decision making by having the right people making the decisions.
This usually means a manager who is in the field and close to the customer rather than an analyst rich in data but poor in experience.
3. Culture
A key responsibility of executives is to shape and manage corporate culture.
The extent to which the BI attitude flourishes in an organization depends in large part on the organization’s culture.
Perhaps the most important step an organization can take to encourage BI is to measure the performance of the organization against a set of key indicators.
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